Climate Change Adaptation Practices Among Smallholder Farmers and Their Implications for Livelihood Sustainability: Evidence from the Bono East Region
Abstract
This
| Metric | Value |
|---|---|
| current_mean | 5419.37 |
| current_median | 4000.00 |
| current_sd | 5870.85 |
| past_mean | 14398.53 |
| past_median | 7000.00 |
| past_sd | 21746.20 |
| mean_change | -8979.17 |
| percent_change | -62.36 |
| income_change | n | percentage |
|---|---|---|
| Decreased significantly | 152 | 41.4 |
| Decreased slightly | 116 | 31.6 |
| Increased significantly | 46 | 12.5 |
| Increased slightly | 45 | 12.3 |
| No change | 8 | 2.2 |
| adaptation_adopted | count | mean_current | median_current | sd_current | mean_past | income_change_amount |
|---|---|---|---|---|---|---|
| No | 74 | 5426.89 | 4000 | 5805.16 | 20282.43 | -14855.54 |
| Yes | 293 | 5417.46 | 4000 | 5897.17 | 12912.49 | -7495.03 |
There is a significant decline in farm incomes over the past five years among smallholder farmers in the Bono East Region.Key summary statistics show:
Current Season Income: Mean of 5,409.80 Cedis, median of 4,000.00 Cedis, standard deviation of 5,865.71 Cedis.
Income 5 Years Ago: Mean of 14,367.42 Cedis, median of 7,000.00 Cedis, standard deviation of 21,724.75 Cedis.
Overall Change: Mean decrease of 8,957.62 Cedis, representing a 62.35% decline.
The distribution of income changes indicates widespread reductions:
Decreased significantly: 153 farmers (41.6%)
Decreased slightly: 116 farmers (31.5%)
Increased significantly: 46 farmers (12.5%)
Increased slightly: 45 farmers (12.2%)
No change: 8 farmers (2.2%)
Violin and boxplot visualizations highlight a narrower and lower income distribution in the current season compared to five years ago, with most farmers reporting lower earnings. Bar plots of income change categories emphasize the dominance of decreases.
When stratified by adaptation strategy adoption:
Farmers without adaptation strategies (n=74): Mean current income 5,426.89 Cedis, mean past income 20,282.43 Cedis, mean change -14,855.54 Cedis.
Farmers with adaptation strategies (n=294): Mean current income 5,405.50 Cedis, mean past income 12,878.61 Cedis, mean change -7,473.11 Cedis.
This suggests that adopters experienced less severe income declines. Violin plots show similar median incomes (4,000 Cedis) but slightly higher variability among adopters, indicating potential benefits from adaptations in mitigating losses.
Production costs per acre exhibit high variability, with an overall mean of 2,039.08 Cedis, median of 1,500.00 Cedis, and standard deviation of 1,854.65 Cedis. The range spans from 200.00 to 12,000.00 Cedis, with 25th percentile at 975.00 Cedis and 75th at 2,500.00 Cedis.Breakdown by cost change and level categories (sorted by count descending).
Bar plots show that cost increases (significantly or slightly) are the most common changes, while high cost levels predominate. Violin plots by cost change category illustrate higher median costs in increasing categories, suggesting escalating expenses as a key challenge.
Scatter plots of production costs vs. current income, colored by cost change, reveal a positive linear trend (dashed regression line), indicating that higher costs often correlate with higher incomes, but with significant scatter, particularly in increasing cost groups.
| production_cost_change | production_cost_level | count | mean_cost_per_acre | median_cost_per_acre |
|---|---|---|---|---|
| Increased significantly | High | 145 | 2294.14 | 2000 |
| Increased slightly | High | 66 | 2285.97 | 2000 |
| Increased significantly | Moderate | 41 | 2135.34 | 1300 |
| No change | High | 21 | 985.71 | 750 |
| Decreased slightly | High | 20 | 1502.80 | 1300 |
| Increased slightly | Moderate | 18 | 2144.44 | 1000 |
| Decreased significantly | High | 15 | 1900.00 | 1500 |
| Decreased slightly | Moderate | 14 | 1347.14 | 1000 |
| No change | Moderate | 9 | 1277.78 | 800 |
| Decreased significantly | Moderate | 6 | 1934.33 | 1250 |
| Decreased slightly | Low | 6 | 1448.00 | 819 |
| Decreased significantly | Low | 3 | 1866.67 | 1800 |
| Increased significantly | Low | 2 | 1500.00 | 1500 |
| No change | Low | 1 | 600.00 | 600 |
| Statistic | Value |
|---|---|
| mean_cost | 2040.28 |
| median_cost | 1500.00 |
| sd_cost | 1857.04 |
| min_cost | 200.00 |
| max_cost | 12000.00 |
| q25 | 950.00 |
| q75 | 2500.00 |
Profit margins were estimated assuming 50 Cedis per bag of yield. Summary by production cost change
| production_cost_change | count | mean_profit_margin | median_profit_margin |
|---|---|---|---|
| Decreased significantly | 19 | 31.56 | 84.00 |
| Decreased slightly | 26 | -143.98 | -17.14 |
| Increased significantly | 160 | -150.10 | 72.50 |
| Increased slightly | 82 | -68.42 | 66.67 |
| No change | 23 | -39.03 | 59.09 |
Notably, significant cost decreases yield positive mean margins, while increases lead to negative means, though medians are often positive, indicating skewed distributions with some profitable outliers. This underscores how rising costs erode sustainability, especially without adaptations.
| soil_fertility_change | n | percentage |
|---|---|---|
| 4 (Significant change) | 152 | 41.4 |
| 3 (Moderate change) | 69 | 18.8 |
| 2 (Slight change) | 44 | 12.0 |
| 1 (No change) | 16 | 4.4 |
| Cause | Count | Percentage |
|---|---|---|
| Overcultivation | 257 | 70.0 |
| Drought | 245 | 66.8 |
| Erosion | 245 | 66.8 |
| Flooding | 95 | 25.9 |
| Others | 15 | 4.1 |
| soil_fertility_change | count_No | count_Yes | percentage_No | percentage_Yes |
|---|---|---|---|---|
| 1 (No change) | 3 | 13 | 4.7 | 6.0 |
| 2 (Slight change) | 2 | 42 | 3.1 | 19.4 |
| 3 (Moderate change) | 13 | 56 | 20.3 | 25.8 |
| 4 (Significant change) | 46 | 106 | 71.9 | 48.8 |
Soil Fertility Findings
Soil fertility changes show prevalent degradation:
Significant change: 153 farmers (41.6%)
Moderate change: 69 farmers (18.8%)
Slight change: 44 farmers (12.0%)
No change: 16 farmers (4.3%)
Primary causes (multiple selections allowed):
Overcultivation: 258 farmers (70.1%) Drought: 245 farmers (66.6%) Erosion: 245 farmers (66.6%) Flooding: 95 farmers (25.8%) Others: 15 farmers (4.1%)
Bar plots visualize the dominance of significant changes and causes like overcultivation and drought/erosion.
By adaptation adoption:
Non-adopters: Significant change (71.9%), Moderate (20.3%), Slight (3.1%), No change (4.7%).
Adopters: Significant change (49.1%), Moderate (25.7%), Slight (19.3%), No change (6.0%).
Adopters report less severe changes, suggesting adaptations mitigate degradation. Clustered bar plots show higher percentages of slight/moderate changes among adopters.
| water_access_change | n | percentage |
|---|---|---|
| No change | 116 | 31.6 |
| Significant decrease | 83 | 22.6 |
| Moderate decrease | 79 | 21.5 |
| Moderate increase | 55 | 15.0 |
| Significant increase | 34 | 9.3 |
| consistent_water_access | n | percentage |
|---|---|---|
| No | 155 | 42.2 |
| Yes | 212 | 57.8 |
| irrigation_access | n | percentage |
|---|---|---|
| No | 168 | 45.8 |
| Yes | 199 | 54.2 |
Water Access
Water access changes indicate mixed but mostly stable or declining patterns:
No change: 116 farmers (31.5%)
Significant decrease: 83 farmers (22.6%)
Moderate decrease: 79 farmers (21.5%)
Moderate increase: 56 farmers (15.2%)
Significant increase: 34 farmers (9.2%)
Consistent water access:No (155 farmers, 42.1%), Yes (213 farmers, 57.9%). Irrigation access: No (168 farmers, 45.7%), Yes (200 farmers, 54.3%).Bar plots highlight no change as most common, with decreases nearly as prevalent. Grouped bar plots of consistency by irrigation show irrigation correlates with more consistent access.
| Indicator | Count | Percentage |
|---|---|---|
| Preferred Foods | 311 | 84.7 |
| Small Meals | 302 | 82.3 |
| Hungry | 272 | 74.1 |
| Variety | 259 | 70.6 |
| Worry | 255 | 69.5 |
| Skip Meals | 254 | 69.2 |
| meals_per_day | count | percentage |
|---|---|---|
| 3 | 252 | 68.7 |
| 2 | 99 | 27.0 |
| 4 | 11 | 3.0 |
| 5 | 4 | 1.1 |
| 1 | 1 | 0.3 |
| food_expenditure_percentage | n | percentage |
|---|---|---|
| 25–50% | 178 | 48.5 |
| 51–75% | 96 | 26.2 |
| Less than 25% | 68 | 18.5 |
| More than 75% — (Ordinal) | 25 | 6.8 |
| consistent_water_access | irrigation_access | count | mean_meals |
|---|---|---|---|
| No | No | 118 | 2.82 |
| No | Yes | 37 | 2.81 |
| Yes | No | 50 | 2.76 |
| Yes | Yes | 162 | 2.74 |
Food security indicators (farmers experiencing issues, multiple allowed):
Preferred Foods: 312 farmers (84.8%)
Small Meals: 303 farmers (82.3%) Hungry: 273 farmers (74.2%) Variety: 260 farmers (70.7%) Worry: 256 farmers (69.6%) Skip Meals: 255 farmers (69.3%)
Preferred foods 84.8% most farmers can’t always eat the foods they want. Small meals 82.3% many reduce portion sizes.
Hungry 74.2% very high hunger prevalence.
Variety 70.7 lack of diet diversity.
Worry 69.6% high anxiety about food availability.
Skip meals 69.3% frequent meal skipping.
Daily meals distribution:
3 meals: 252 farmers (68.5%)
2 meals: 99 farmers (26.9%)
4 meals: 11 farmers (3.0%)
5 meals: 4 farmers (1.1%)
1 meal: 1 farmer (0.3%)
Food expenditure as percentage of income: 25–50%: 179 farmers (48.6%) 51–75%: 96 farmers (26.1%) Less than 25%: 68 farmers (18.5%) More than 75%: 25 farmers (6.8%)
Bar plots show high prevalence of concerns like limited preferred foods and small meals, with most farmers at 3 meals/day and moderate expenditure.
Water access vs. food security:No consistent access, No irrigation: 118 farmers, mean meals 2.82
No consistent access, Yes irrigation: 37 farmers, mean meals 2.81
Yes consistent access, No irrigation: 50 farmers, mean meals 2.76
Yes consistent access, Yes irrigation: 162 farmers, mean meals 2.74
Boxplots indicate slightly higher meals with irrigation, regardless of consistency, suggesting irrigation supports better food security.
| Variable1 | Variable2 | Correlation |
|---|---|---|
| avg_production_cost_per_acre | income_last_season | 0.246 |
| avg_production_cost_per_acre | meals_per_day | -0.177 |
| crop_area_acres_or_hectares | meals_per_day | -0.173 |
| crop_area_acres_or_hectares | farming_experience_years | 0.114 |
| farming_experience_years | income_last_season | 0.102 |
| income_last_season | meals_per_day | -0.097 |
| crop_area_acres_or_hectares | current_yield_bags_or_acre | 0.087 |
| avg_production_cost_per_acre | current_yield_bags_or_acre | 0.085 |
| crop_area_acres_or_hectares | income_last_season | 0.083 |
| current_yield_bags_or_acre | income_last_season | -0.079 |
The strongest positive correlation is between production costs and current income (0.246), while negative links appear between costs/area and meals per day (-0.177 and -0.173), implying higher inputs/scale may strain food security. The correlation matrix plot visually reinforces these moderate relationships, with no extremely strong correlations, highlighting multifaceted influences on livelihoods. Overall, findings link climate-induced challenges ( soil/water degradation) to economic pressures, with adaptations offering partial resilience for sustainability.
| Aspect | Key_Finding |
|---|---|
| Farm Income | Mean income (Cedis): 5419 |
| Production Costs | Mean cost per acre (Cedis): 2040 |
| Soil Fertility | 54.1% report significant decline |
| Water Access | 42.2% lack consistent access |
| Food Security | Mean meals per day: 2.8 |
| flooding_frequency | n | percentage |
|---|---|---|
| Never | 236 | 64.3 |
| Sometimes | 59 | 16.1 |
| Rarely | 38 | 10.4 |
| Often | 21 | 5.7 |
| Always | 13 | 3.5 |
| flooding_impact_frequency | n | percentage |
|---|---|---|
| Never | 230 | 62.7 |
| Sometimes | 59 | 16.1 |
| Rarely | 49 | 13.4 |
| Often | 17 | 4.6 |
| Always | 12 | 3.3 |
| flooding_severity | n | percentage |
|---|---|---|
| Low | 244 | 66.5 |
| Moderate | 83 | 22.6 |
| High | 40 | 10.9 |
| flooding_incidence_change | n | percentage |
|---|---|---|
| No Change | 159 | 43.3 |
| Slight Increase | 64 | 17.4 |
| Moderate Increase | 57 | 15.5 |
| Very Significant Increase | 47 | 12.8 |
| Significant Increase | 40 | 10.9 |
The analysis of flooding frequency among smallholder farmers reveals that a majority experience minimal flooding events.
The distribution is as follows:
Never: 236 farmers (64.3%)
Sometimes: 59 farmers (16.1%)
Rarely: 38 farmers (10.4%)
Often: 21 farmers (5.7%)
Always: 13 farmers (3.5%)
Bar plots illustrate “Never” as the dominant category, with frequencies tapering off toward more regular occurrences. This suggests that while flooding is not ubiquitous, a notable subset of farmers (about 35.7%) face it to varying degrees, potentially linked to climate change variability in the Bono East Region.
Flooding Impact Frequency
The frequency of flooding impacts on farming operations shows even lower prevalence, indicating that not all flooding events result in significant disruptions:
Never: 230 farmers (62.7%)
Sometimes: 59 farmers (16.1%)
Rarely: 49 farmers (13.4%)
Often: 17 farmers (4.6%)
Always: 12 farmers (3.3%)
Visualizations via bar plots highlight “Never” as the most common, with “Sometimes” and “Rarely” accounting for the bulk of occasional impacts. This implies resilience in some systems but vulnerability where impacts do occur.
Flooding Severity
When flooding does occur, its severity is generally low to moderate
Low: 244 farmers (66.5%)
Moderate: 83 farmers (22.6%)
High: 40 farmers (10.9%)
Bar plots emphasize the predominance of low severity, suggesting that while flooding happens, extreme cases are less common, possibly due to local topography or adaptive measures.
Changes in Flooding Incidence Over Time Perceptions of changes in flooding incidence over time indicate stability or mild increases:
No Change: 159 farmers (43.3%)
Slight Increase: 64 farmers (17.4%)
Moderate Increase: 57 farmers (15.5%)
Very Significant Increase: 47 farmers (12.8%)
Significant Increase: 40 farmers (10.9%)
Bar plots show “No Change” as the leading response, but over half report some increase, aligning with climate change trends of intensified hydrological events.
| flooding_frequency | flooding_severity | count | mean_yield | median_yield | sd_yield |
|---|---|---|---|---|---|
| Never | Low | 208 | 1374.48 | 15.0 | 6072.37 |
| Sometimes | Moderate | 28 | 1335.76 | 22.0 | 5980.67 |
| Rarely | Moderate | 22 | 14285735.86 | 16.0 | 36313642.82 |
| Never | Moderate | 20 | 802.35 | 27.0 | 2202.56 |
| Sometimes | Low | 17 | 21201.73 | 602.0 | 28569.08 |
| Sometimes | High | 14 | 4640.15 | 30.0 | 11115.80 |
| Rarely | Low | 13 | 7049.62 | 40.0 | 17148.65 |
| Often | Moderate | 12 | 46.80 | 54.0 | 16.10 |
| Always | High | 8 | 145.00 | 10.0 | 235.56 |
| Never | High | 8 | 155.14 | 16.0 | 249.40 |
| Often | High | 7 | 760.50 | 20.0 | 1493.09 |
| Always | Low | 4 | 5000.00 | 5000.0 | 0.00 |
| Rarely | High | 3 | 16.00 | 16.0 | NA |
| Often | Low | 2 | 12.50 | 12.5 | 10.61 |
| Always | Moderate | 1 | NaN | NA | NA |
| flooding_frequency | count | mean_income | median_income | sd_income |
|---|---|---|---|---|
| Never | 236 | 5815.17 | 4500 | 5899.71 |
| Sometimes | 59 | 5711.41 | 4000 | 7844.24 |
| Often | 21 | 4857.14 | 5000 | 2471.35 |
| Rarely | 38 | 3540.79 | 3000 | 3479.89 |
| Always | 13 | 3308.08 | 2500 | 2151.30 |
Relationship Between Flooding and Yield
Higher frequency and severity tend to associate with erratic yields, though medians suggest more stable lower outputs in frequent flooding scenarios. This highlights flooding’s disruptive potential on productivity.
14,285,735.86, indicate data issues
Relationship Between Flooding and Income
ncome analysis by flooding frequency (sorted by mean income descending) shows an inverse relationship, with less frequent flooding linked to higher earning
Violin and boxplots depict narrower income distributions and lower
medians in higher frequency categories, indicating economic
vulnerability from recurrent flooding.
Flooding is cited as a cause of soil degradation by 95 farmers (25.9%), while 272 (74.1%) do not attribute it as such. This moderate association suggests flooding contributes to erosion and fertility loss but is not the primary driver.
Cross-tabulation of flooding frequency vs. soil fertility changes:
| soil_degradation_cause_flooding | count | percentage |
|---|---|---|
| 0 | 272 | 74.1 |
| 1 | 95 | 25.9 |
| flooding_frequency | n_1 (No change) | n_4 (Significant change) | n_2 (Slight change) | n_3 (Moderate change) | percentage_1 (No change) | percentage_4 (Significant change) | percentage_2 (Slight change) | percentage_3 (Moderate change) |
|---|---|---|---|---|---|---|---|---|
| Always | 6 | 5 | 0 | 0 | 54.5 | 45.5 | 0.0 | 0.0 |
| Never | 7 | 117 | 19 | 24 | 4.2 | 70.1 | 11.4 | 14.4 |
| Often | 1 | 7 | 4 | 4 | 6.2 | 43.8 | 25.0 | 25.0 |
| Rarely | 0 | 10 | 4 | 21 | 0.0 | 28.6 | 11.4 | 60.0 |
| Sometimes | 2 | 13 | 17 | 20 | 3.8 | 25.0 | 32.7 | 38.5 |
Clustered bar plots show higher frequencies correlate with more significant fertility changes, though “Never” has high significant change percentages, possibly due to other factors.
Adopters are more prevalent in higher frequency categories ( 18.1% in “Sometimes” vs. 8.1% non-adopters), suggesting adaptations are responsive to flooding risks.Among adopters (n=293, but table uses 294 from prior; assuming similar), flood-related strategies:Crop Diversification: 91 farmers (31.1%) Drought Flood Resistant (varieties): 69 farmers (23.5%) Rainwater Harvesting: 26 farmers (8.9%) Agroforestry: 18 farmers (6.1%)
Bar plots and clustered visuals indicate higher adoption rates in frequent flooding groups, with crop diversification as the most common strategy for resilience.
| flooding_frequency | n_No | n_Yes | percentage_No | percentage_Yes |
|---|---|---|---|---|
| Always | 3 | 10 | 4.1 | 3.4 |
| Never | 48 | 188 | 64.9 | 64.2 |
| Often | 4 | 17 | 5.4 | 5.8 |
| Rarely | 13 | 25 | 17.6 | 8.5 |
| Sometimes | 6 | 53 | 8.1 | 18.1 |
| Strategy | Count | Percentage |
|---|---|---|
| Crop Diversification | 91 | 31.1 |
| Drought Flood Resistant | 69 | 23.5 |
| Rainwater Harvesting | 26 | 8.9 |
| Agroforestry | 18 | 6.1 |
Higher frequencies link to lower mean meals and higher worry/skipping rates, except “Rarely” showing better outcomes.
| flooding_frequency | count | mean_meals | worried_about_food | skipped_meals | worried_percentage | skipped_percentage |
|---|---|---|---|---|---|---|
| Always | 13 | 2.69 | 11 | 7 | 84.6 | 53.8 |
| Never | 236 | 2.78 | 155 | 137 | 65.7 | 58.1 |
| Often | 21 | 2.76 | 18 | 13 | 85.7 | 61.9 |
| Rarely | 38 | 2.97 | 25 | 11 | 65.8 | 28.9 |
| Sometimes | 59 | 2.66 | 46 | 37 | 78.0 | 62.7 |
| flooding_frequency | food_expenditure_percentage | n | percentage |
|---|---|---|---|
| Always | 25–50% | 2 | 15.4 |
| Always | 51–75% | 11 | 84.6 |
| Never | 25–50% | 117 | 49.6 |
| Never | 51–75% | 52 | 22.0 |
| Never | Less than 25% | 46 | 19.5 |
| Never | More than 75% — (Ordinal) | 21 | 8.9 |
| Often | 25–50% | 14 | 66.7 |
| Often | 51–75% | 4 | 19.0 |
| Often | Less than 25% | 2 | 9.5 |
| Often | More than 75% — (Ordinal) | 1 | 4.8 |
| Rarely | 25–50% | 14 | 36.8 |
| Rarely | 51–75% | 13 | 34.2 |
| Rarely | Less than 25% | 8 | 21.1 |
| Rarely | More than 75% — (Ordinal) | 3 | 7.9 |
| Sometimes | 25–50% | 31 | 52.5 |
| Sometimes | 51–75% | 16 | 27.1 |
| Sometimes | Less than 25% | 12 | 20.3 |
| Variable1 | Variable2 | Correlation |
|---|---|---|
| flooding_freq_numeric | flooding_severity_numeric | 0.522 |
| flooding_severity_numeric | flooding_freq_numeric | 0.522 |
| income_last_season | avg_production_cost_per_acre | 0.246 |
| avg_production_cost_per_acre | income_last_season | 0.246 |
| meals_per_day | flooding_freq_numeric | -0.241 |
| flooding_freq_numeric | meals_per_day | -0.241 |
| crop_area_acres_or_hectares | flooding_freq_numeric | 0.180 |
| flooding_freq_numeric | crop_area_acres_or_hectares | 0.180 |
| avg_production_cost_per_acre | meals_per_day | -0.177 |
| meals_per_day | avg_production_cost_per_acre | -0.177 |
| meals_per_day | crop_area_acres_or_hectares | -0.173 |
| crop_area_acres_or_hectares | meals_per_day | -0.173 |
| avg_production_cost_per_acre | flooding_freq_numeric | 0.158 |
| flooding_freq_numeric | avg_production_cost_per_acre | 0.158 |
| farming_experience_years | crop_area_acres_or_hectares | 0.114 |
Strongest is between flooding frequency and severity (0.522), with negative ties to meals per day (-0.241) and positive to costs/area, underscoring flooding’s role in eroding sustainability. Overall, findings portray flooding as a growing threat impacting yields, incomes, soil, and food security, with adaptations like crop diversification offering mitigation, though adoption is uneven.